This presentation discusses Spring Data Elasticsearch, an open source project for integrating Elasticsearch with Spring applications. It provides an overview of key features like configuring Elasticsearch clients, defining entities, performing CRUD and search operations using repositories, and customizing behaviors through callbacks. The presenter encourages contributions to the community-driven project and provides contact details for further information.
A walkthrough the main principles to reach solid NodeJS Applications with TypeScript language, Jest as Test Runner and NestJS as framework for structure.
FIWARE Training: Introduction to Smart Data ModelsFIWARE
The document introduces the Smart Data Models program which provides standardized data models for various domains. It explains that the program aims to enable agile standardization through contributions from the community. It outlines the governance structure and current status of the program, including the available domains, data models, contributors and tools. Participants are then guided through an exercise to turn a data source into a Smart Data Model by generating a JSON schema, example payload and submitting it as a pull request to the incubated repository on GitHub.
MongoDB is an open-source, document-oriented database that provides high performance and horizontal scalability. It uses a document-model where data is organized in flexible, JSON-like documents rather than rigidly defined rows and tables. Documents can contain multiple types of nested objects and arrays. MongoDB is best suited for applications that need to store large amounts of unstructured or semi-structured data and benefit from horizontal scalability and high performance.
Redis is an open source, in-memory data structure store that can be used as a database, cache, or message broker. It supports data structures like strings, hashes, lists, sets, sorted sets with ranges and pagination. Redis provides high performance due to its in-memory storage and support for different persistence options like snapshots and append-only files. It uses client/server architecture and supports master-slave replication, partitioning, and failover. Redis is useful for caching, queues, and other transient or non-critical data.
This document provides an overview of API gateways and their role in microservice architectures. It begins with a brief history of monolithic architectures and how microservices emerged as a solution. It then defines key concepts like APIs, gateways, and how they relate. The main points are:
1) An API gateway acts as a single entry point and centralizes request routing, protocol translation, and provides cross-cutting features like authentication, monitoring and security for internal microservices.
2) Gateways help reduce complexity and overhead by encapsulating microservices and allowing transformations, while also improving reusability and security.
3) Examples of API gateway tools are provided, as well as a proposed activity, before concluding
Comparison between Oracle JDK, Oracle OpenJDK, and Red Hat OpenJDK
Oracle JDK SE Public Updates
Oracle JDK SE Support Roadmap (LTS options)
Oracle JDK licenses
Oracle JDK vs Oracle OpenJDK
Java SE Release Roadmap
The OpenJDK build is free to use within a Red Hat Enterprise Linux (RHEL)
The Red Hat OpenJDK Features
A walkthrough the main principles to reach solid NodeJS Applications with TypeScript language, Jest as Test Runner and NestJS as framework for structure.
FIWARE Training: Introduction to Smart Data ModelsFIWARE
The document introduces the Smart Data Models program which provides standardized data models for various domains. It explains that the program aims to enable agile standardization through contributions from the community. It outlines the governance structure and current status of the program, including the available domains, data models, contributors and tools. Participants are then guided through an exercise to turn a data source into a Smart Data Model by generating a JSON schema, example payload and submitting it as a pull request to the incubated repository on GitHub.
MongoDB is an open-source, document-oriented database that provides high performance and horizontal scalability. It uses a document-model where data is organized in flexible, JSON-like documents rather than rigidly defined rows and tables. Documents can contain multiple types of nested objects and arrays. MongoDB is best suited for applications that need to store large amounts of unstructured or semi-structured data and benefit from horizontal scalability and high performance.
Redis is an open source, in-memory data structure store that can be used as a database, cache, or message broker. It supports data structures like strings, hashes, lists, sets, sorted sets with ranges and pagination. Redis provides high performance due to its in-memory storage and support for different persistence options like snapshots and append-only files. It uses client/server architecture and supports master-slave replication, partitioning, and failover. Redis is useful for caching, queues, and other transient or non-critical data.
This document provides an overview of API gateways and their role in microservice architectures. It begins with a brief history of monolithic architectures and how microservices emerged as a solution. It then defines key concepts like APIs, gateways, and how they relate. The main points are:
1) An API gateway acts as a single entry point and centralizes request routing, protocol translation, and provides cross-cutting features like authentication, monitoring and security for internal microservices.
2) Gateways help reduce complexity and overhead by encapsulating microservices and allowing transformations, while also improving reusability and security.
3) Examples of API gateway tools are provided, as well as a proposed activity, before concluding
Comparison between Oracle JDK, Oracle OpenJDK, and Red Hat OpenJDK
Oracle JDK SE Public Updates
Oracle JDK SE Support Roadmap (LTS options)
Oracle JDK licenses
Oracle JDK vs Oracle OpenJDK
Java SE Release Roadmap
The OpenJDK build is free to use within a Red Hat Enterprise Linux (RHEL)
The Red Hat OpenJDK Features
The document compares NoSQL and SQL databases. It notes that NoSQL databases are non-relational and have dynamic schemas that can accommodate unstructured data, while SQL databases are relational and have strict, predefined schemas. NoSQL databases offer more flexibility in data structure, but SQL databases provide better support for transactions and data integrity. The document also discusses differences in queries, scaling, and consistency between the two database types.
Power Your Predictive Analytics with InfluxDBInfluxData
If you're using InfluxDB to store and manage your time series data, you're already off to a great start. But why stop there? In our upcoming webinar, we'll show you how to take your data analysis to the next level by building predictive analytics using a variety of tools and techniques.
We will demonstrate how to use Quix to create custom dashboards and visualizations that allow you to monitor your data in real-time. We'll also introduce you to Hugging Face, a powerful tool for building models that can predict future trends and identify anomalies. With these tools at your disposal, you'll be able to extract valuable insights from your data and make more informed decisions about the future. Don't miss out on this opportunity to improve your data analysis skills and take your business to the next level!
What you will learn:
Use InfluxDB to store and manage time series data
Utilize Quix and Hugging Face to build models, visualize trends, and identify anomalies
Extract valuable insights from your data
Improve your data analysis skills to make informed decision
When it comes to Large Scale data processing and Machine Learning, Apache Spark is no doubt one of the top battle-tested frameworks out there for handling batched or streaming workloads. The ease of use, built-in Machine Learning modules, and multi-language support makes it a very attractive choice for data wonks. However bootstrapping and getting off the ground could be difficult for most teams without leveraging a Spark cluster that is already pre-provisioned and provided as a managed service in the Cloud, while this is a very attractive choice to get going, in the long run, it could be a very expensive option if it’s not well managed.
As an alternative to this approach, our team has been exploring and working a lot with running Spark and all our Machine Learning workloads and pipelines as containerized Docker packages on Kubernetes. This provides an infrastructure-agnostic abstraction layer for us, and as a result, it improves our operational efficiency and reduces our overall compute cost. Most importantly, we can easily target our Spark workload deployment to run on any major Cloud or On-prem infrastructure (with Kubernetes as the common denominator) by just modifying a few configurations.
In this talk, we will walk you through the process our team follows to make it easy for us to run a production deployment of our Machine Learning workloads and pipelines on Kubernetes which seamlessly allows us to port our implementation from a local Kubernetes set up on the laptop during development to either an On-prem or Cloud Kubernetes environment
FIWARE Wednesday Webinars - Introduction to NGSI-LDFIWARE
Introduction to NGSI-LD Webinar - 27th May 2020
Corresponding webinar recording: https://youtu.be/rZ13IyLpAtA
A data-model driven and linked data first introduction for developers to NGSI-LD and JSON-LD.
Chapter: Core
Difficulty: 3
Audience: Any Technical
Presenter: Jason Fox (Senior Technical Evangelist, FIWARE Foundation)
London In-Memory Computing Meetup - A Change-Data-Capture use-case: designing...Nicolas Fränkel
When one’s app is challenged with poor performances, it’s easy to set up a cache in front of one’s SQL database. It doesn’t fix the root cause (e.g. bad schema design, bad SQL query, etc.) but it gets the job done. If the app is the only component that writes to the underlying database, it’s a no-brainer to update the cache accordingly, so the cache is always up-to-date with the data in the database.
Things start to go sour when the app is not the only component writing to the DB. Among other sources of writes, there are batches, other apps (shared databases exist, unfortunately), etc. One might think about a couple of ways to keep data in sync i.e. polling the DB every now and then, DB triggers, etc. Unfortunately, they all have issues that make them unreliable and/or fragile.
In this talk, I will describe an easy-to-setup architecture that leverages CDC to have an evergreen cache.
Conférence Devoxx FR 2022
"Microservices, DDD et bootstrapping pour faire un départ lancé"
Résumé de la présentation :
Associer microservices et conception DDD (Domain-Driven Design) semble une évidence. Le découpage en contextes et les différentes couches d’architecture constituent un cadre séduisant pour bâtir des microservices avec une structure stéréotypée. Mais si on souhaite respecter les fondamentaux du DDD et garantir l’isolation des différentes couches on arrive rapidement à une structure de projet basée sur plusieurs modules qui peuvent devenir complexes à gérer et qui risquent de ralentir le cycle de développement, en particulier lors de la phase de démarrage.
Cette présentation est un retour d’expérience d’un grand projet dans lequel le générateur de code Telosys a été utilisé pour automatiser la phase d’amorçage de chaque microservice.
Environnement technique : Java, SpringBoot, Telosys
Kibana is a data visualization tool that is part of the ELK stack (Elasticsearch, Logstash, Kibana) and allows users to search, analyze, and visualize data stored in Elasticsearch. The document discusses Kibana's essential features including Discover to query data, Visualize to create visualizations, and Dashboard to combine them. It also covers additional tools like Dev Tools, X-Pack plugins, and Machine Learning capabilities.
Elastic Agent is a single, unified way to add monitoring to systems and services through integrations. It is managed through Fleet, which provides a centralized UI for defining Elastic Agent policies that specify which integrations to run on which hosts. Fleet Server connects Elastic Agents to Fleet and handles distributing policies and collecting states. The Elastic Package Registry hosts integrations that can be used by Elastic Agent.
by Mahesh Pakal, AWS
PostgreSQL is a powerful, enterprise class open source object-relational database system with an emphasis on extensibility and standards-compliance. PostgreSQL boasts many sophisticated features and runs stored procedures in more than a dozen programming languages. We’ll explore the advantages and limitations of PostgreSQL, examples of where it is best suited for use, and examples of who is using PostgreSQL to power their applications.
The document provides instructions for deploying Prometheus and the Kube Prometheus Stack on NKS. Key steps include:
1. Deploying Prometheus using Helm with custom storage class and service type settings.
2. Verifying successful deployment by checking pods, services, and accessing the Prometheus UI.
3. Deploying the Kube Prometheus Stack using Helm, again with custom storage class and service type settings.
4. Verifying successful deployment including checking pods, services, and accessing the Grafana UI with default credentials to view pre-configured dashboards importing from Prometheus data.
This document discusses using JSON in Oracle Database 18c/19c. It begins by introducing the presenter and their background. It then covers storing and querying JSON in the database using various SQL and PL/SQL features like JSON_QUERY, JSON_OBJECT, and JSON_TABLE. The document discusses how different SQL data types are converted to JSON. It shows examples of converting rows to CSV, XML, and JSON formats for data exchange. In summary, the document provides an overview of Oracle Database's support for JSON focusing on using it properly for data exchange and storage.
GraphQL is a query language for APIs and a runtime for fulfilling those queries. It gives clients the power to ask for exactly what they need, which makes it a great fit for modern web and mobile apps. In this talk, we explain why GraphQL was created, introduce you to the syntax and behavior, and then show how to use it to build powerful APIs for your data. We will also introduce you to AWS AppSync, a GraphQL-powered serverless backend for apps, which you can use to host GraphQL APIs and also add real-time and offline capabilities to your web and mobile apps. You can follow along if you have an AWS account – no GraphQL experience required!
Level: Beginner
Speaker: Rohan Deshpande - Sr. Software Dev Engineer, AWS Mobile Applications
Listen up, developers. You are not special. Your infrastructure is not a beautiful and unique snowflake. You have the same tech debt as everyone else. This is a talk about a better way to build and manage infrastructure: Terraform Modules. It goes over how to build infrastructure as code, package that code into reusable modules, design clean and flexible APIs for those modules, write automated tests for the modules, and combine multiple modules into an end-to-end techs tack in minutes.
You can find the video here: https://www.youtube.com/watch?v=LVgP63BkhKQ
This document provides an overview and introduction to NoSQL databases. It begins with an agenda that explores key-value, document, column family, and graph databases. For each type, 1-2 specific databases are discussed in more detail, including their origins, features, and use cases. Key databases mentioned include Voldemort, CouchDB, MongoDB, HBase, Cassandra, and Neo4j. The document concludes with references for further reading on NoSQL databases and related topics.
Telosys project booster Paris Open Source Summit 2019Laurent Guérin
Telosys is a code generation tool that allows developers to generate repetitive code automatically from models and templates, saving significant time. It uses lightweight models defined in text files or from a database schema to represent project entities. Templates written in the Velocity Template Language are used to generate specific code files for different targets from the model. The generated code is customizable and independent of Telosys. It aims to accelerate development without requiring major strategic decisions by being easy to use and remove if desired.
Telosys tutorial - Code generation for a Python web application based on Bott...Laurent Guérin
Telosys CLI tutorial - How to generate a Python web application based on Bottle, SQLAlchemy and SQLite
Installation, model setup, bundles of templates, code generation and tests
This document discusses migrating from Java 8 to Java 11. It outlines changes between Java versions, such as modularization and removal of deprecated modules. It provides tips for migration such as updating dependencies, resolving illegal access warnings, and using Docker for testing. Resources are shared for learning more about migrating applications and libraries to newer Java versions.
Eland: A Python client for data analysis and explorationElasticsearch
Python is a highly adopted language for data science and analysis. Eland is a Python client and toolkit for DataFrames, big data, machine learning, and ETL in Elasticsearch. Get an introduction to Eland with a hands-on demo where you’ll learn about the DataFrame implementation of Eland, as well as how to manage machine learning models.
The importance of normalizing your security data to ECSElasticsearch
The Elastic Common Schema (ECS) can be used for SIEM, logging, APM, and more. See the different paths to adopting ECS for security and why data normalization is so critical. Learn how to map custom sources so they can be used by Elastic Security and how to implement custom pipelines that may require additional fields. We'll provide concrete examples and give pointers to relevant resources to help you get going.
The document compares NoSQL and SQL databases. It notes that NoSQL databases are non-relational and have dynamic schemas that can accommodate unstructured data, while SQL databases are relational and have strict, predefined schemas. NoSQL databases offer more flexibility in data structure, but SQL databases provide better support for transactions and data integrity. The document also discusses differences in queries, scaling, and consistency between the two database types.
Power Your Predictive Analytics with InfluxDBInfluxData
If you're using InfluxDB to store and manage your time series data, you're already off to a great start. But why stop there? In our upcoming webinar, we'll show you how to take your data analysis to the next level by building predictive analytics using a variety of tools and techniques.
We will demonstrate how to use Quix to create custom dashboards and visualizations that allow you to monitor your data in real-time. We'll also introduce you to Hugging Face, a powerful tool for building models that can predict future trends and identify anomalies. With these tools at your disposal, you'll be able to extract valuable insights from your data and make more informed decisions about the future. Don't miss out on this opportunity to improve your data analysis skills and take your business to the next level!
What you will learn:
Use InfluxDB to store and manage time series data
Utilize Quix and Hugging Face to build models, visualize trends, and identify anomalies
Extract valuable insights from your data
Improve your data analysis skills to make informed decision
When it comes to Large Scale data processing and Machine Learning, Apache Spark is no doubt one of the top battle-tested frameworks out there for handling batched or streaming workloads. The ease of use, built-in Machine Learning modules, and multi-language support makes it a very attractive choice for data wonks. However bootstrapping and getting off the ground could be difficult for most teams without leveraging a Spark cluster that is already pre-provisioned and provided as a managed service in the Cloud, while this is a very attractive choice to get going, in the long run, it could be a very expensive option if it’s not well managed.
As an alternative to this approach, our team has been exploring and working a lot with running Spark and all our Machine Learning workloads and pipelines as containerized Docker packages on Kubernetes. This provides an infrastructure-agnostic abstraction layer for us, and as a result, it improves our operational efficiency and reduces our overall compute cost. Most importantly, we can easily target our Spark workload deployment to run on any major Cloud or On-prem infrastructure (with Kubernetes as the common denominator) by just modifying a few configurations.
In this talk, we will walk you through the process our team follows to make it easy for us to run a production deployment of our Machine Learning workloads and pipelines on Kubernetes which seamlessly allows us to port our implementation from a local Kubernetes set up on the laptop during development to either an On-prem or Cloud Kubernetes environment
FIWARE Wednesday Webinars - Introduction to NGSI-LDFIWARE
Introduction to NGSI-LD Webinar - 27th May 2020
Corresponding webinar recording: https://youtu.be/rZ13IyLpAtA
A data-model driven and linked data first introduction for developers to NGSI-LD and JSON-LD.
Chapter: Core
Difficulty: 3
Audience: Any Technical
Presenter: Jason Fox (Senior Technical Evangelist, FIWARE Foundation)
London In-Memory Computing Meetup - A Change-Data-Capture use-case: designing...Nicolas Fränkel
When one’s app is challenged with poor performances, it’s easy to set up a cache in front of one’s SQL database. It doesn’t fix the root cause (e.g. bad schema design, bad SQL query, etc.) but it gets the job done. If the app is the only component that writes to the underlying database, it’s a no-brainer to update the cache accordingly, so the cache is always up-to-date with the data in the database.
Things start to go sour when the app is not the only component writing to the DB. Among other sources of writes, there are batches, other apps (shared databases exist, unfortunately), etc. One might think about a couple of ways to keep data in sync i.e. polling the DB every now and then, DB triggers, etc. Unfortunately, they all have issues that make them unreliable and/or fragile.
In this talk, I will describe an easy-to-setup architecture that leverages CDC to have an evergreen cache.
Conférence Devoxx FR 2022
"Microservices, DDD et bootstrapping pour faire un départ lancé"
Résumé de la présentation :
Associer microservices et conception DDD (Domain-Driven Design) semble une évidence. Le découpage en contextes et les différentes couches d’architecture constituent un cadre séduisant pour bâtir des microservices avec une structure stéréotypée. Mais si on souhaite respecter les fondamentaux du DDD et garantir l’isolation des différentes couches on arrive rapidement à une structure de projet basée sur plusieurs modules qui peuvent devenir complexes à gérer et qui risquent de ralentir le cycle de développement, en particulier lors de la phase de démarrage.
Cette présentation est un retour d’expérience d’un grand projet dans lequel le générateur de code Telosys a été utilisé pour automatiser la phase d’amorçage de chaque microservice.
Environnement technique : Java, SpringBoot, Telosys
Kibana is a data visualization tool that is part of the ELK stack (Elasticsearch, Logstash, Kibana) and allows users to search, analyze, and visualize data stored in Elasticsearch. The document discusses Kibana's essential features including Discover to query data, Visualize to create visualizations, and Dashboard to combine them. It also covers additional tools like Dev Tools, X-Pack plugins, and Machine Learning capabilities.
Elastic Agent is a single, unified way to add monitoring to systems and services through integrations. It is managed through Fleet, which provides a centralized UI for defining Elastic Agent policies that specify which integrations to run on which hosts. Fleet Server connects Elastic Agents to Fleet and handles distributing policies and collecting states. The Elastic Package Registry hosts integrations that can be used by Elastic Agent.
by Mahesh Pakal, AWS
PostgreSQL is a powerful, enterprise class open source object-relational database system with an emphasis on extensibility and standards-compliance. PostgreSQL boasts many sophisticated features and runs stored procedures in more than a dozen programming languages. We’ll explore the advantages and limitations of PostgreSQL, examples of where it is best suited for use, and examples of who is using PostgreSQL to power their applications.
The document provides instructions for deploying Prometheus and the Kube Prometheus Stack on NKS. Key steps include:
1. Deploying Prometheus using Helm with custom storage class and service type settings.
2. Verifying successful deployment by checking pods, services, and accessing the Prometheus UI.
3. Deploying the Kube Prometheus Stack using Helm, again with custom storage class and service type settings.
4. Verifying successful deployment including checking pods, services, and accessing the Grafana UI with default credentials to view pre-configured dashboards importing from Prometheus data.
This document discusses using JSON in Oracle Database 18c/19c. It begins by introducing the presenter and their background. It then covers storing and querying JSON in the database using various SQL and PL/SQL features like JSON_QUERY, JSON_OBJECT, and JSON_TABLE. The document discusses how different SQL data types are converted to JSON. It shows examples of converting rows to CSV, XML, and JSON formats for data exchange. In summary, the document provides an overview of Oracle Database's support for JSON focusing on using it properly for data exchange and storage.
GraphQL is a query language for APIs and a runtime for fulfilling those queries. It gives clients the power to ask for exactly what they need, which makes it a great fit for modern web and mobile apps. In this talk, we explain why GraphQL was created, introduce you to the syntax and behavior, and then show how to use it to build powerful APIs for your data. We will also introduce you to AWS AppSync, a GraphQL-powered serverless backend for apps, which you can use to host GraphQL APIs and also add real-time and offline capabilities to your web and mobile apps. You can follow along if you have an AWS account – no GraphQL experience required!
Level: Beginner
Speaker: Rohan Deshpande - Sr. Software Dev Engineer, AWS Mobile Applications
Listen up, developers. You are not special. Your infrastructure is not a beautiful and unique snowflake. You have the same tech debt as everyone else. This is a talk about a better way to build and manage infrastructure: Terraform Modules. It goes over how to build infrastructure as code, package that code into reusable modules, design clean and flexible APIs for those modules, write automated tests for the modules, and combine multiple modules into an end-to-end techs tack in minutes.
You can find the video here: https://www.youtube.com/watch?v=LVgP63BkhKQ
This document provides an overview and introduction to NoSQL databases. It begins with an agenda that explores key-value, document, column family, and graph databases. For each type, 1-2 specific databases are discussed in more detail, including their origins, features, and use cases. Key databases mentioned include Voldemort, CouchDB, MongoDB, HBase, Cassandra, and Neo4j. The document concludes with references for further reading on NoSQL databases and related topics.
Telosys project booster Paris Open Source Summit 2019Laurent Guérin
Telosys is a code generation tool that allows developers to generate repetitive code automatically from models and templates, saving significant time. It uses lightweight models defined in text files or from a database schema to represent project entities. Templates written in the Velocity Template Language are used to generate specific code files for different targets from the model. The generated code is customizable and independent of Telosys. It aims to accelerate development without requiring major strategic decisions by being easy to use and remove if desired.
Telosys tutorial - Code generation for a Python web application based on Bott...Laurent Guérin
Telosys CLI tutorial - How to generate a Python web application based on Bottle, SQLAlchemy and SQLite
Installation, model setup, bundles of templates, code generation and tests
This document discusses migrating from Java 8 to Java 11. It outlines changes between Java versions, such as modularization and removal of deprecated modules. It provides tips for migration such as updating dependencies, resolving illegal access warnings, and using Docker for testing. Resources are shared for learning more about migrating applications and libraries to newer Java versions.
Eland: A Python client for data analysis and explorationElasticsearch
Python is a highly adopted language for data science and analysis. Eland is a Python client and toolkit for DataFrames, big data, machine learning, and ETL in Elasticsearch. Get an introduction to Eland with a hands-on demo where you’ll learn about the DataFrame implementation of Eland, as well as how to manage machine learning models.
The importance of normalizing your security data to ECSElasticsearch
The Elastic Common Schema (ECS) can be used for SIEM, logging, APM, and more. See the different paths to adopting ECS for security and why data normalization is so critical. Learn how to map custom sources so they can be used by Elastic Security and how to implement custom pipelines that may require additional fields. We'll provide concrete examples and give pointers to relevant resources to help you get going.
See the vision for the future of Elastic solutions, from new features to GovCloud availability and FedRAMP authorization. Find out what’s in store for Elastic Enterprise Search, Observability, and Security and see how they’re evolving to help users better mitigate risk, reduce costs, and modernize infrastructures. Plus, see the honorees for this year’s Elastic Search Public Sector Awards and learn about their projects.
Finding relevant results faster with ElasticsearchElasticsearch
With today's growing amounts of information, it's critical to be able to efficiently retrieve the most relevant results for a query. Learn how Elasticsearch finds top hits for a query so quickly by building inverted indexes and using the Block-MAX WAND algorithm, as well as how you can tune Elasticsearch to make it even more efficient for your own use cases.
Get tips directly from the experts at Elastic about planning for, monitoring, and troubleshooting the Elastic Stack at scale. Elastic experts will share the tools, strategies, and architectures that can be used to ensure cluster health and performance. Learn about using tools like automated alerting to identify and remediate issues rapidly. Walk away armed with best practices for how to ensure both cluster and data resiliency.
Breaking silos between DevOps and SecOps with ElasticElasticsearch
What is better: 99.999% uptime, continuous delivery, or a secure environment? Yeah, we had the same reaction: “Why do I need to pick one?” With Elastic, your operations and security teams can work together on a single platform, and help drive mean time to detect/resolve to zero for both operational and security issues. Hear how we are helping customers break down artificial silos between teams and use cases, and move towards a DevSecOps culture.
How we built this: Data tiering, snapshots, and asynchronous searchElasticsearch
What goes into a major roadmap investment at Elastic? Take a closer look at the technical capabilities that come together to help us deliver on our data tier vision — from asynchronous search to searchable S3/blob store/Google storage, new cold and frozen storage tiers, and more.
Developers use the Elastic API, CLI, and SDK to automate deployment provisioning, operations, and programmatic scaling. If you're looking to embed these functions into your CI/CD pipelines, applications, shell scripts, infrastructure as code (IaC) tools such as Terraform, or even configuration management tools like Ansible, Chef, and Puppet — this session is for you.
From secure VPC links to SSO with Elastic CloudElasticsearch
Have you ever wondered how you can use the technologies built into Elastic Cloud to improve your deployment's security posture? Learn about security best practices for built-in security features such as encryption by default for data in transit or at rest, and also the tools you can use to enhance security such as IP filtering and our AWS PrivateLink integration.
Migrating to Elasticsearch Service on Elastic CloudElasticsearch
Learn how to get started with migrating your cluster to Elastic Cloud. Hear about the best practices and strategies for migrating your clusters and data to Elastic Cloud. The topics we'll cover include deployment sizing, indexing your data, restoring from snapshots, and more.
This document introduces Visualforce for building mobile applications. It discusses how device usage is shifting to mobile and users need simple, fast interfaces. It demonstrates using jQuery Mobile and JavaScript remoting to build responsive mobile apps that interface with Salesforce data. The Mobile SDK is presented as a tool to accelerate development of native, hybrid and HTML5 apps with features like OAuth, APIs, offline storage and push notifications. Debugging mobile apps is also briefly covered, along with new Visualforce components for mobile.
Elasticsearch: From development to production in 15 minutesElasticsearch
One of the great hallmarks of using Elasticsearch, especially on Elastic Cloud, is the ability to move at warp speed when putting something into production. Get a walkthrough on how to get up and running with Elasticsearch in real time and learn tips for how to make sure your Elasticsearch clusters are ready to meet the demands of your organization.
1) The Salesforce1 Platform allows developers to build apps using core services like Chatter, Analytics, and APIs.
2) Developers can use declarative tools like workflows, visualforce, and formula fields or program with Apex.
3) Apex is Salesforce's programming language that allows developers to extend functionality with custom objects, logic, and integrations using HTTP callouts.
SIEM, malware protection, deep data visibility — for freeElasticsearch
Are you a SIEM user who needs endpoint detection and correlation for complex multi-stage attacks across your environment? Elastic has launched a free and open endpoint security offering, directly integrated into the Elastic Stack. This offering is part of the free distribution tier and is available to every Elastic user. Learn how Elastic Security can help you protect your environment and why this advancement is so significant to security visibility.
Autoscaling: From zero to production seamlesslyElasticsearch
Have you ever wanted to seamlessly scale up and down the size of your Elastic deployment? Autoscaling is coming to Elastic. Learn how this upcoming feature will help simplify the management of your deployments and how you can automatically scale up and down as demand increases or decreases. We’ll describe how Elasticsearch determines when it is time to scale up or down, and how that information is communicated through the platform.
Streamline search with Elasticsearch Service on Microsoft AzureElasticsearch
Join Microsoft and learn about the best practices of running Elasticsearch Service in the Azure cloud, and how the partnership with Elastic makes it easier for you to deploy powerful search experiences in your Azure environment. You will also see joint service demos and hear about shared enterprise customer success stories.
Streamline search with Elasticsearch Service on Microsoft AzureElasticsearch
Join Microsoft and learn about the best practices of running Elasticsearch Service in the Azure cloud, and how the partnership with Elastic makes it easier for you to deploy powerful search experiences in your Azure environment. You will also see joint service demos and hear about shared enterprise customer success stories.
This presentation discusses securing the Elastic Stack for free. It provides an overview of how security features have evolved from separate plugins to being integrated and enabled by default. It then summarizes the three main steps to enable security: obtaining TLS certificates, configuring passwords, and enabling security in Elasticsearch. Finally, it discusses how role-based access control and Kibana spaces can be used to implement authorization and multitenancy.
Learn why Elastic Cloud is the best place to run everything Elastic. You will hear about our commitment to the cloud, the benefits of using managed services, and the optimizations we’ve made for running in public clouds. Listen as IST Research discusses their success with Elastic and see an end-to-end demo showing how easy it is to get started.
Creating stellar customer support experiences using searchElasticsearch
Customers, now more than ever, want to solve support issues on their own using websites and mobile applications. And self-service customer support translates to reduced support costs and higher customer satisfaction. Learn how Elastic Enterprise Search helps you achieve all this and more.
Similar to Next-level integration with Spring Data Elasticsearch (20)
An introduction to Elasticsearch's advanced relevance ranking toolboxElasticsearch
The hallmark of a great search experience is always delivering the most relevant results, quickly, to every user. The difficulty lies behind the scenes in making that happen elegantly and at a scale. From App Search’s intuitive drag and drop interface to the advanced relevance capabilities built into the core of Elasticsearch — Elastic offers a range of tools for developers to tune relevance ranking and create incredible search experiences. In this session, we’ll explore some of Elasticsearch’s advanced relevance ranking features, such as dense vector fields, BM25F, ranking evaluation, and more. Plus we’ll give you some ideas for how these features are being used by other Elastic users to create world-class, category defining search experiences.
Eze Castle Integration is a managed service provider (MSP), cloud service provider (CSP), and internet service provider (ISP) that delivers services to more than 1,000 clients around the world. Different departments within Eze Castle have devised their own log aggregation solutions in order to provide visibility, meet regulatory compliance requirements, conduct cybersecurity investigations, and help engineers with troubleshooting infrastructure issues. In 2019, they partnered with Elastic to consolidate the data generated from different systems into a single pane of glass. And thanks to the ease of deployment on Elastic Cloud, professional consultation services from Elastic engineers, and on-demand training courses available on Elastic Learning, Eze Castle was able to go from proof-of-concept to a fully functioning ""Eze Managed SIEM"" product within a month!
Learn about Eze Castle's journey with Elastic and how they grew Eze Managed SIEM from zero to 100 customers In less than 14 months.
Cómo crear excelentes experiencias de búsqueda en sitios webElasticsearch
Descubre lo fácil que es crear búsquedas relevantes y enriquecidas en sitios web de cara al público para impulsar las conversiones, incrementar el consumo de contenido y ayudar a los visitantes a encontrar lo que necesitan. Realiza un recorrido por las herramientas de Elastic a las que puedes sacar partido para transformar con facilidad tu sitio web, lo que incluye nuestro nuevo y potente rastreador web.
Te damos la bienvenida a una nueva forma de realizar búsquedas Elasticsearch
1) The document introduces ElasticON Solution Series, which provides out-of-the-box personalized, centralized, and secure organizational search across internal and external sources.
2) It discusses how Elastic Enterprise Search can improve productivity, satisfaction, collaboration, and decision making by connecting all applications and content with a single scalable search platform.
3) The solution achieves this through intuitive search features, powerful analytics and visualization tools, simplified administration, and security certifications to ensure data protection.
Tirez pleinement parti d'Elastic grâce à Elastic CloudElasticsearch
Découvrez pourquoi Elastic Cloud est la solution idéale pour exploiter toutes les offres d'Elastic. Bénéficiez d'une flexibilité d'achat et de déploiement au sein de Google Cloud, de Microsoft Azure, d'Amazon Web Services ou des trois à la fois. Apprenez quels avantages vous apporte une offre de service géré et déterminez la solution qui vous permet de la gérer par vous-même grâce à des outils intégrés d'automatisation et d'orchestration. Et ce n'est pas tout ! Familiarisez-vous avec les fonctionnalités qui peuvent vous aider à scaler vos opérations au fur et à mesure de l'évolution de votre déploiement, à stocker vos données d'une manière rentable et à optimiser vos recherches. Ainsi, vous n'aurez plus à abandonner de données et obtiendrez les informations exploitables dont vous avez besoin pour assurer le fonctionnement de votre entreprise.
Comment transformer vos données en informations exploitablesElasticsearch
Découvrez des fonctionnalités stratégiques de la Suite Elastic, notamment Elasticsearch, un moteur de données incomparable, et Kibana, véritable fenêtre ouverte sur la Suite Elastic.
Dans cette session, vous apprendrez à :
injecter des données dans la Suite Elastic ;
stocker des données ;
analyser des données ;
exploiter des données.
Plongez au cœur de la recherche dans tous ses états.Elasticsearch
À l'instar de la plupart des entreprises modernes, vos équipes utilisent probablement plus de 10 applications hébergées dans le cloud chaque jour, mais passent aussi bien trop de temps à chercher les informations dont elles ont besoin dans ces outils. Grâce aux fonctionnalités prêtes à l'emploi d'Elastic Workplace Search, découvrez combien il est facile de mettre le contenu pertinent à portée de la main de vos équipes grâce à une recherche unifiée sur l'ensemble des applications qu'elles utilisent pour faire leur travail.
Modernising One Legal Se@rch with Elastic Enterprise Search [Customer Story]Elasticsearch
Knowledge management needs in the legal sector, why Linklaters decided to move away from its legacy KM search engine, Kin+Carta's management of the migration process, and how the switch revitalised a well-established system and opened up new possibilities for its future development.
An introduction to Elasticsearch's advanced relevance ranking toolboxElasticsearch
The hallmark of a great search experience is always delivering the most relevant results, quickly, to every user. The difficulty lies behind the scenes in making that happen elegantly and at a scale. From App Search’s intuitive drag and drop interface to the advanced relevance capabilities built into the core of Elasticsearch — Elastic offers a range of tools for developers to tune relevance ranking and create incredible search experiences. In this session, we’ll explore some of Elasticsearch’s advanced relevance ranking features, such as dense vector fields, BM25F, ranking evaluation, and more. Plus we’ll give you some ideas for how these features are being used by other Elastic users to create world-class, category defining search experiences.
Like most modern organizations, your teams are likely using upwards of 10 cloud-based applications on a daily basis, but spending far too many hours a day searching for the information they need across all of them. With the out-of-the-box capabilities of Elastic Workplace Search, see how easy it is to put relevant content right at your teams’ fingertips with unified search across all the apps they rely on to get work done.
Building great website search experiencesElasticsearch
Discover how easy it is to create rich, relevant search on public facing websites that drives conversion, increases content consumption, and helps visitors find what they need. Get a tour of the Elastic tools you can leverage to easily transform your website, including our powerful new web crawler.
Keynote: Harnessing the power of Elasticsearch for simplified searchElasticsearch
Get an overview of the innovation Elastic is bringing to the Enterprise Search landscape, and learn how you can harness these capabilities across your technology landscape to make the power of search work for you.
Cómo transformar los datos en análisis con los que tomar decisionesElasticsearch
Descubre las áreas de características estratégicas de Elastic Stack: Elasticsearch, un motor de datos inigualable y Kibana, la ventana que da acceso a Elastic Stack.
En la sesión hablaremos sobre:
Cómo incorporar datos a Elastic Stack
Almacenamiento de datos
Análisis de los datos
Actuar en función de los datos
Explore relève les défis Big Data avec Elastic Cloud Elasticsearch
Spécialisée dans le développement et la gestion de solutions de veille documentaire et commerciale, Explore offre à ses clients une lecture précise et organisée de l’actualités des marchés et projets sur leurs territoires d'intervention. Afin de rendre leur offre plus agile et performante, Explore a choisi l’offre Elastic Cloud hébergée sur Microsoft Azure. Découvrez comment les équipes de production et de développement sont désormais en mesure de mieux exploiter les données pour les clients d’Explore et gagnent du temps sur la gestion de leur infrastructure.
Comment transformer vos données en informations exploitablesElasticsearch
Découvrez des fonctionnalités stratégiques de la Suite Elastic, notamment Elasticsearch, un moteur de données incomparable, et Kibana, véritable fenêtre ouverte sur la Suite Elastic.
Dans cette session, vous apprendrez à :
injecter des données dans la Suite Elastic ;
stocker des données ;
analyser des données ;
exploiter des données.
Transforming data into actionable insightsElasticsearch
Learn about the strategic feature areas of the Elastic Stack—Elasticsearch, a data engine like no other, and Kibana, the window into the Elastic Stack.
The session will cover:
Bringing data into the Elastic Stack
Storing data
Analyzing data
Acting on data
"Elastic enables the world’s leading organization to exceed their business objectives and power their mission-critical systems by eliminating data silos, connecting the dots, and transforming data of all types into actionable insights.
Come learn how the power of search can help you quickly surface relevant insights at scale. Whether you are an executive looking to reduce operational costs, a department head striving to do more with fewer tools, or engineer monitoring and protecting your IT environment, this session is for you. "
Empowering agencies using Elastic as a Service inside GovernmentElasticsearch
It has now been four years since the beta release of Elastic Cloud Enterprise which kicked off a wave of the Elastic public sector community running Elastic as a service within Government rather than utilizing purely hosted solutions. Fast forward to 2021 and we have multiple options for multiple mission needs. Learn top tips from Elastic architects and their experience enabling their teams with the automation and provisioning of Elastic tech to change the game in how government delivers solutions.
The opportunities and challenges of data for public goodElasticsearch
The document discusses data for public good and the opportunities and challenges involved. It notes that data infrastructure is needed to deliver public good through data. There are almost endless opportunities to use data for public services, policy, and citizen benefits. However, challenges include legacy systems, data silos, unclear governance, and risk aversion. As a case study, it outlines how the UK Census 2021 addressed index faced challenges but showed progress on using data better, with lessons for continued public sector transformation.
"Scaling RAG Applications to serve millions of users", Kevin GoedeckeFwdays
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
"What does it really mean for your system to be available, or how to define w...Fwdays
We will talk about system monitoring from a few different angles. We will start by covering the basics, then discuss SLOs, how to define them, and why understanding the business well is crucial for success in this exercise.
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Introducing BoxLang : A new JVM language for productivity and modularity!Ortus Solutions, Corp
Just like life, our code must adapt to the ever changing world we live in. From one day coding for the web, to the next for our tablets or APIs or for running serverless applications. Multi-runtime development is the future of coding, the future is to be dynamic. Let us introduce you to BoxLang.
Dynamic. Modular. Productive.
BoxLang redefines development with its dynamic nature, empowering developers to craft expressive and functional code effortlessly. Its modular architecture prioritizes flexibility, allowing for seamless integration into existing ecosystems.
Interoperability at its Core
With 100% interoperability with Java, BoxLang seamlessly bridges the gap between traditional and modern development paradigms, unlocking new possibilities for innovation and collaboration.
Multi-Runtime
From the tiny 2m operating system binary to running on our pure Java web server, CommandBox, Jakarta EE, AWS Lambda, Microsoft Functions, Web Assembly, Android and more. BoxLang has been designed to enhance and adapt according to it's runnable runtime.
The Fusion of Modernity and Tradition
Experience the fusion of modern features inspired by CFML, Node, Ruby, Kotlin, Java, and Clojure, combined with the familiarity of Java bytecode compilation, making BoxLang a language of choice for forward-thinking developers.
Empowering Transition with Transpiler Support
Transitioning from CFML to BoxLang is seamless with our JIT transpiler, facilitating smooth migration and preserving existing code investments.
Unlocking Creativity with IDE Tools
Unleash your creativity with powerful IDE tools tailored for BoxLang, providing an intuitive development experience and streamlining your workflow. Join us as we embark on a journey to redefine JVM development. Welcome to the era of BoxLang.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Lee Barnes - Path to Becoming an Effective Test Automation Engineer.pdfleebarnesutopia
So… you want to become a Test Automation Engineer (or hire and develop one)? While there’s quite a bit of information available about important technical and tool skills to master, there’s not enough discussion around the path to becoming an effective Test Automation Engineer that knows how to add VALUE. In my experience this had led to a proliferation of engineers who are proficient with tools and building frameworks but have skill and knowledge gaps, especially in software testing, that reduce the value they deliver with test automation.
In this talk, Lee will share his lessons learned from over 30 years of working with, and mentoring, hundreds of Test Automation Engineers. Whether you’re looking to get started in test automation or just want to improve your trade, this talk will give you a solid foundation and roadmap for ensuring your test automation efforts continuously add value. This talk is equally valuable for both aspiring Test Automation Engineers and those managing them! All attendees will take away a set of key foundational knowledge and a high-level learning path for leveling up test automation skills and ensuring they add value to their organizations.
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...DanBrown980551
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
2. 2
This presentation and the accompanying oral presentation contain forward-looking statements, including statements
concerning plans for future offerings; the expected strength, performance or benefits of our offerings; and our future
operations and expected performance. These forward-looking statements are subject to the safe harbor provisions
under the Private Securities Litigation Reform Act of 1995. Our expectations and beliefs in light of currently
available information regarding these matters may not materialize. Actual outcomes and results may differ materially
from those contemplated by these forward-looking statements due to uncertainties, risks, and changes in
circumstances, including, but not limited to those related to: the impact of the COVID-19 pandemic on our business
and our customers and partners; our ability to continue to deliver and improve our offerings and successfully
develop new offerings, including security-related product offerings and SaaS offerings; customer acceptance and
purchase of our existing offerings and new offerings, including the expansion and adoption of our SaaS offerings;
our ability to realize value from investments in the business, including R&D investments; our ability to maintain and
expand our user and customer base; our international expansion strategy; our ability to successfully execute our
go-to-market strategy and expand in our existing markets and into new markets, and our ability to forecast customer
retention and expansion; and general market, political, economic and business conditions.
Additional risks and uncertainties that could cause actual outcomes and results to differ materially are included in
our filings with the Securities and Exchange Commission (the “SEC”), including our Annual Report on Form 10-K for
the most recent fiscal year, our quarterly report on Form 10-Q for the most recent fiscal quarter, and any
subsequent reports filed with the SEC. SEC filings are available on the Investor Relations section of Elastic’s
website at ir.elastic.co and the SEC’s website at www.sec.gov.
Any features or functions of services or products referenced in this presentation, or in any presentations, press
releases or public statements, which are not currently available or not currently available as a general availability
release, may not be delivered on time or at all. The development, release, and timing of any features or functionality
described for our products remains at our sole discretion. Customers who purchase our products and services
should make the purchase decisions based upon services and product features and functions that are currently
available.
All statements are made only as of the date of the presentation, and Elastic assumes no obligation to, and does not
currently intend to, update any forward-looking statements or statements relating to features or functions of services
or products, except as required by law.
Forward-Looking Statements
3. 3
Nothing will stop you being creative more
effectively as the fear of making a mistake.
John Cleese
6. “Spring Data’s mission is to provide a
familiar and consistent, Spring-based
programming model for data access
while still retaining the special traits of
the underlying data store.”